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17 materials found

Authors: allegra.via Via  or Boris Steipe 


Exploratory Analysis of Biological Data using R 2018

Course covered for this workshop are broadly relevant for many areas of modern, quantitative biology such as flow cytometry, expression profile analysis, function prediction and more.

Introduction to R 2018

Course introduces essential ideas and tools of R, and covers statistical tests in R.

Exploratory Analysis of Biological Data using R 2017 Module 5-Hypothesis Testing

Course covers essential tools and strategies that are available for EDA through the free statistical workbench R.

Exploratory Analysis of Biological Data using R 2017 Module 4-Clustering

Course covers essential tools and strategies that are available for EDA through the free statistical workbench R.

Exploratory Analysis of Biological Data using R 2017 Module 3-Dimension Reduction

Course covers essential tools and strategies that are available for EDA through the free statistical workbench R.

Exploratory Analysis of Biological Data using R 2017 Module 2-Regression

Course covers essential tools and strategies that are available for EDA through the free statistical workbench R.

Exploratory Analysis of Biological Data using R 2017 Module 1-Exploratory Data Analysis

Course covers essential tools and strategies that are available for EDA through the free statistical workbench R.

Introduction to R 2017

Course covers the bioinformatics tools available for meeting the challenges of data handling and breaking down problems into structured parts using R.

Introduction to Biopython

This is a module from the "Python for Biologists" course. The module presents an introduction to Biopython. It shows how to deal with sequences and sequence records, how to download records from NCBI databases, how to run Blast and how to parse XML Blast outputs.

Keywords: Bioinformatics, Biopython, Programming, Python, Python biologists

Using R with Python

This is a module from the "Python for Biologists" course. It describes the Python module interfacing the R package for statistics. The module shows how to calculate mean, standard deviation, z-score and p-value of a set of numbers, and how to generate plots. Input files for the scripts presented...

Keywords: Programming, Python, Python biologists

Searching data using Python

This is a module from the "Python for Biologists" course. It describes how to use Python dictionary and set data structures to search your data. In particular, how to use a dictionary to represent the genetic code table and use it to translate a nucleotide sequence into a protein sequence, and...

Keywords: Programming, Python, Python biologists

Pattern Matching

This is a module from the "Python for Biologists" course. It teaches how to do pattern matching in Python, i.e. how to find a substring (or a set of substrings) in a string. To this aim, it introduces the regular expression syntax, and the tools needed to search regular expressions in biological...

Keywords: Pattern matching, Programming, Python, Python biologists

Writing functions in Python programming

This is a module from the "Python for Biologists" course. It deals with functions and how to write and use them. It also introduces namespaces and the tuple data structure. The module contains several exercises and suggested solutions. The text of exercises is also provided in a separate file. 

Scientific topics: Bioinformatics

Keywords: Programming, Python, Python biologists

Python Programs

This is a module from the "Python for Biologists" course. It deals with Python programs, how to write and run them, and how to provide input and generate output. The module also contains exercises and suggested solutions. 

Keywords: Programming, Python, Python biologists

Linear Motifs and Phosphorylation Sites

This is a lecture on linear motifs and phophorylation sites (P-sites). Some materials from other lectures are reused.
The lecture is basically about computational approaches to encode, predict, analyse, and use functional motifs and P-sites.
Here you can find:

    A definition of linear motifs and...

Keywords: Bioinformatics

Parsing data records using Python programming

This is a module from the "Python for Biologists" course. One typical problem in bioinformatics is parsing data files. This module explains how to parse FASTA files and GenBank records. It also introduces the if/elif/else construct to make choice in programming and the list  data structure. The...

Keywords: Bioinformatics, Programming, Python, Python biologists, Record parsing

Introduction to Unix

Introductory lecture to the Unix/Linux command-line

    Description of the computer shell and the command-line interface

    Differences between graphical and command-line interfaces

    The most commond Unix/Linux commands are provided

 
 

Keywords: Bioinformatics, Programming, Unixlinux